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BackgroundWearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated. ObjectiveThis study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA). MethodsFor the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis. ResultsA total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day. ConclusionsThis study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period. International Registered Report Identifier (IRRID)RR2-10.2196/10238

BackgroundThe huge increase in smartphone use heralds an enormous opportunity for epidemiology research, but there is limited evidence regarding long-term engagement and attrition in mobile health (mHealth) studies. ObjectiveThe objective of this study was to examine how representative the Cloudy with a Chance of Pain study population is of wider chronic-pain populations and to explore patterns of engagement among participants during the first 6 months of the study. MethodsParticipants in the United Kingdom who had chronic pain (≥3 months) and enrolled between January 20, 2016 and January 29, 2016 were eligible if they were aged ≥17 years and used the study app to report any of 10 pain-related symptoms during the study period. Participant characteristics were compared with data from the Health Survey for England (HSE) 2011. Distinct clusters of engagement over time were determined using first-order hidden Markov models, and participant characteristics were compared between the clusters. ResultsCompared with the data from the HSE, our sample comprised a higher proportion of women (80.51%, 5129/6370 vs 55.61%, 4782/8599) and fewer persons at the extremes of age (16-34 and 75+). Four clusters of engagement were identified: high (13.60%, 865/6370), moderate (21.76%, 1384/6370), low (39.35%, 2503/6370), and tourists (25.44%, 1618/6370), between which median days of data entry ranged from 1 (interquartile range; IQR: 1-1; tourist) to 149 (124-163; high). Those in the high-engagement cluster were typically older, whereas those in the tourist cluster were mostly male. Few other differences distinguished the clusters. ConclusionsCloudy with a Chance of Pain demonstrates a rapid and successful recruitment of a large, representative, and engaged sample of people with chronic pain and provides strong evidence to suggest that smartphones could provide a viable alternative to traditional data collection methods.

BackgroundThe increasing ownership of smartphones provides major opportunities for epidemiological research through self-reported and passively collected data. ObjectiveThis pilot study aimed to codesign a smartphone app to assess associations between weather and joint pain in patients with rheumatoid arthritis (RA) and to study the success of daily self-reported data entry over a 60-day period and the enablers of and barriers to data collection. MethodsA patient and public involvement group (n=5) and 2 focus groups of patients with RA (n=9) supported the codesign of the app collecting self-reported symptoms. A separate “capture app” was designed to collect global positioning system (GPS) and continuous raw accelerometer data, with the GPS-linking providing local weather data. A total of 20 patients with RA were then recruited to collect daily data for 60 days, with entry and exit interviews. Of these, 17 were loaned an Android smartphone, whereas 3 used their own Android smartphones. ResultsOf the 20 patients, 6 (30%) withdrew from the study: 4 because of technical challenges and 2 for health reasons. The mean completion of daily entries was 68% over 2 months. Patients entered data at least five times per week 65% of the time. Reasons for successful engagement included a simple graphical user interface, automated reminders, visualization of data, and eagerness to contribute to this easily understood research question. The main barrier to continuing engagement was impaired battery life due to the accelerometer data capture app. For some, successful engagement required ongoing support in using the smartphones. ConclusionsThis successful pilot study has demonstrated that daily data collection using smartphones for health research is feasible and achievable with high levels of ongoing engagement over 2 months. This result opens important opportunities for large-scale longitudinal epidemiological research.

Objectives Epidemiological estimates of psoriatic arthritis (PsA) underpin the provision of healthcare, research, and the work of government, charities and patient organizations. Methodological problems impacting prior estimates include small sample sizes, incomplete case ascertainment, and representativeness. We developed a statistical modelling strategy to provide contemporary prevalence and incidence estimates of PsA from 1991 to 2020 in the UK. Methods Data from Clinical Practice Research Datalink (CPRD) were used to identify cases of PsA between 1st January 1991 and 31st December 2020. To optimize ascertainment, we identified cases of Definite PsA (≥1 Read code for PsA) and Probable PsA (satisfied a bespoke algorithm). Standardized annual rates were calculated using Bayesian multilevel regression with post-stratification to account for systematic differences between CPRD data and the UK population, based on age, sex, socioeconomic status and region of residence. Results A total of 26 293 recorded PsA cases (all definitions) were identified within the study window (77.9% Definite PsA). Between 1991 and 2020 the standardized prevalence of PsA increased twelve-fold from 0.03–0.37. The standardized incidence of PsA per 100 000 person years increased from 8.97 in 1991–15.08 in 2020, an almost 2-fold increase. Over time, rates were similar between the sexes, and across socioeconomic status. Rates were strongly associated with age, and consistently highest in Northern Ireland. Conclusion The prevalence and incidence of PsA recorded in primary care has increased over the last three decades. The modelling strategy presented can be used to provide contemporary prevalence estimates for musculoskeletal disease using routinely collected primary care data. [ABSTRACT FROM AUTHOR]

Objectives Pain, fatigue and sleep disturbances are common symptoms in patients with rheumatic and musculoskeletal diseases (RMDs) that may prompt the use of over-the-counter (OTC) supplements, sleep aids and analgesics as self-management strategies. This study evaluated the prevalence of OTC supplements, sleep aids and pain relievers and the financial burden associated with their use in rheumatology. Methods A web-based survey developed with patients was administered in rheumatology clinics in an English hospital. Participants shared demographic information and detailed their use of OTC supplements, sleep aids and pain relief in the past week. The data were analysed using descriptive statistics and logistic regression models to identify influencing factors. Results A total of 876 people consented to participate in the survey. More than half of patients (54.5%) reported daily supplement intake, typically spending £10/month (interquartile range 5–20), ranging up to £200/month. The most commonly administered supplements were vitamin D, multivitamins, vitamin C, vitamin B/B complex and omega-3/-6 supplements, with multiple overlaps. Prescription, OTC or non-prescription pain relief use was reported by 82% of respondents, with sleep aids being used by 13%. Of the 327 patients who took NSAIDs, 165 (50.4%) also reported taking OTC supplements, while among the 131 patients using opioids (20.5%), 66 (50.3%) reported supplement use, some of which have documented interactions. Conclusion The use of OTC supplements, pain relief and sleep aids is common in patients with RMDs. Healthcare professionals should be encouraged to proactively ask about these during consultations, especially from a drug safety perspective, but also to provide timely, reliable advice about such strategies that may be sought by patients. [ABSTRACT FROM AUTHOR]

Rationale Aims and Objectives Method Results Conclusion Patients with rheumatoid arthritis (RA) experience a range of symptoms including joint pain and inflammation, stiffness, fatigue, anxiety, and low mood. Similar to patients with other long‐term conditions, they may have periods of time when their disease is under control, and times when their condition is less stable, requiring treatment adjustments. The REMORA2 feasibility study explored the implementation of an integrated symptom‐tracking system using a smartphone application (app), enabling patients to track day‐to‐day symptoms. The data was available in the electronic health record to be viewed at subsequent consultations.This paper explores patients' comments on living with RA, and how patient‐reported symptom data supports informed interactions as patients and clinicians work together to coproduce meaning from the data.Individual semi‐structured interviews were conducted with 21 patients and 7 clinicians, supplemented by nonparticipant observations of 5 clinical appointments. Thematic analysis was used to analyse data from the interviews, with an ethnographic approach used to analyse the observational data.Both clinicians and patients reported the benefits of reviewing the data in the clinic together. This helped inform decisions about pain management and identified patients who might otherwise have dismissed symptoms such as pain, because of their natural inclination to be stoical.Improved insights on the care of RA were generated as patients and clinicians discuss symptom tracking data. This can assist the patient‐clinician dyad in the process of two‐way learning and shared decision‐making on the management of a long‐term condition. [ABSTRACT FROM AUTHOR]

Background: Opioids administered in hospital during the immediate postoperative period are likely to influence post-surgical outcomes, but inpatient prescribing during the admission is challenging to access. Modified-release(MR) preparations have been especially associated with harm, whilst certain populations such as the elderly or those with renal impairment may be vulnerable to complications. This study aimed to assess postoperative opioid utilisation patterns during hospital stay for people admitted for major/orthopaedic surgery. Methods: Patients admitted to a teaching hospital in the North-West of England between 2010–2021 for major/orthopaedic surgery with an admission for ≥1 day were included. We examined opioid administrations in the first seven days post-surgery in hospital, and "first 48 hours" were defined as the initial period. Proportions of MR opioids, initial immediate-release(IR) oxycodone and initial morphine milligram equivalents (MME)/day were calculated and summarised by calendar year. We also assessed the proportion of patients prescribed an opioid at discharge. Results: Among patients admitted for major/orthopaedic surgery, 71.1% of patients administered opioids during their hospitalisation. In total 50,496 patients with 60,167 hospital admissions were evaluated. Between 2010–2017 MR opioids increased from 8.7% to 16.1% and dropped to 11.6% in 2021. Initial use of oxycodone IR among younger patients (≤70 years) rose from 8.3% to 25.5% (2010–2017) and dropped to 17.2% in 2021. The proportion of patients on ≥50MME/day ranged from 13% (2021) to 22.9% (2010). Of the patients administered an opioid in hospital, 26,920 (53.3%) patients were discharged on an opioid. Conclusions: In patients hospitalised with major/orthopaedic surgery, 4 in 6 patients were administered an opioid. We observed a high frequency of administered MR opioids in adult patients and initial oxycodone IR in the ≤70 age group. Patients prescribed with ≥50MME/day ranged between 13–22.9%. This is the first published study evaluating UK inpatient opioid use, which highlights opportunities for improving safer prescribing in line with latest recommendations. [ABSTRACT FROM AUTHOR]

Objective To investigate opioid prescribing trends and assess the impact of the COVID-19 pandemic on opioid prescribing in rheumatic and musculoskeletal diseases (RMDs). Methods Adult patients with RA, PsA, axial spondyloarthritis (AxSpA), SLE, OA and FM with opioid prescriptions between 1 January 2006 and 31 August 2021 without cancer in UK primary care were included. Age- and gender-standardized yearly rates of new and prevalent opioid users were calculated between 2006 and 2021. For prevalent users, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006 and 2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of prevalent opioid users between January 2015 and August 2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. Results The study included 1 313 519 RMD patients. New opioid users for RA, PsA and FM increased from 2.6, 1.0 and 3.4/10 000 persons in 2006 to 4.5, 1.8 and 8.7, respectively, in 2018 or 2019. This was followed by a fall to 2.4, 1.2 and 5.9, respectively, in 2021. Prevalent opioid users for all RMDs increased from 2006 but plateaued or dropped beyond 2018, with a 4.5-fold increase in FM between 2006 and 2021. In this period, MME/day increased for all RMDs, with the highest for FM (≥35). During COVID-19 lockdowns, RA, PsA and FM showed significant changes in the trend of prevalent opioid users. The trend for FM increased pre-pandemic and started decreasing during the pandemic. Conclusion The plateauing or decreasing trend of opioid users for RMDs after 2018 may reflect the efforts to tackle rising opioid prescribing in the UK. The pandemic led to fewer people on opioids for most RMDs, providing reassurance that there was no sudden increase in opioid prescribing during the pandemic. [ABSTRACT FROM AUTHOR]

Author(s): Meghna Jani 1,2, Nadyne Girard 3,4, David W. Bates 5,6,7, David L. Buckeridge 3,4, Therese Sheppard 1, Jack Li 8,9, Usman Iqbal 8,9, Shelly Vik 10,11, Colin Weaver 10,11, [...], Background The opioid epidemic in North America has been driven by an increase in the use and potency of prescription opioids, with ensuing excessive opioid-related deaths. Internationally, there are lower rates of opioid-related mortality, possibly because of differences in prescribing and health system policies. Our aim was to compare opioid prescribing rates in patients without cancer, across 5 centers in 4 countries. In addition, we evaluated differences in the type, strength, and starting dose of medication and whether these characteristics changed over time. Methods and findings We conducted a retrospective multicenter cohort study of adults who are new users of opioids without prior cancer. Electronic health records and administrative health records from Boston (United States), Quebec and Alberta (Canada), United Kingdom, and Taiwan were used to identify patients between 2006 and 2015. Standard dosages in morphine milligram equivalents (MMEs) were calculated according to The Centers for Disease Control and Prevention. Age- and sex-standardized opioid prescribing rates were calculated for each jurisdiction. Of the 2,542,890 patients included, 44,690 were from Boston (US), 1,420,136 Alberta, 26,871 Quebec (Canada), 1,012,939 UK, and 38,254 Taiwan. The highest standardized opioid prescribing rates in 2014 were observed in Alberta at 66/1,000 persons compared to 52, 51, and 18/1,000 in the UK, US, and Quebec, respectively. The median MME/day (IQR) at initiation was highest in Boston at 38 (20 to 45); followed by Quebec, 27 (18 to 43); Alberta, 23 (9 to 38); UK, 12 (7 to 20); and Taiwan, 8 (4 to 11). Oxycodone was the first prescribed opioid in 65% of patients in the US cohort compared to 14% in Quebec, 4% in Alberta, 0.1% in the UK, and none in Taiwan. One of the limitations was that data were not available from all centers for the entirety of the 10-year period. Conclusions In this study, we observed substantial differences in opioid prescribing practices for non-cancer pain between jurisdictions. The preference to start patients on higher MME/day and more potent opioids in North America may be a contributing cause to the opioid epidemic.

The authors reflect on the need for healthcare professionals in writing directly to patients about his or her healthcare. Topics discussed include the standard practice in involving patients in outpatient clinical letters in the United Kingdom, the objective of writing directly to patients, and the contents of clinical letters.

Background: Although many people are supportive of their deidentified health care data being used for research, concerns about privacy, safety, and security of health care data remain. There is low awareness about how data are used for research and related governance. Transparency about how health data are used for research is crucial for building public trust. One proposed solution is to ensure that affected communities are notified, particularly marginalized communities where there has previously been a lack of engagement and mistrust. Objective: This study aims to explore patient and public perspectives on the use of deidentified data from electronic health records for musculoskeletal research and to explore ways to build and sustain public trust in health data sharing for a research program (known as "the Data Jigsaw") piloting new ways of using and analyzing electronic health data. Views and perspectives about how best to engage with local communities informed the development of a public notification campaign about the research. Methods: Qualitative methods data were generated from 20 semistructured interviews and 8 focus groups, comprising 48 participants in total with musculoskeletal conditions or symptoms, including 3 carers. A presentation about the use of health data for research and examples from the specific research projects within the program were used to trigger discussion. We worked in partnership with a patient and public involvement group throughout the research and cofacilitated wider community engagement. Results: Respondents were supportive of their health care data being shared for research purposes, but there was low awareness about how electronic health records are used for research. Security and governance concerns about data sharing were noted, including collaborations with external companies and accessing social care records. Project examples from the Data Jigsaw program were viewed positively after respondents knew more about how their data were being used to improve patient care. A range of different methods to build and sustain trust were deemed necessary by participants. Information was requested about: data management; individuals with access to the data (including any collaboration with external companies); the National Health Service's national data opt-out; and research outcomes. It was considered important to enable in-person dialogue with affected communities in addition to other forms of information. Conclusions: The findings have emphasized the need for transparency and awareness about health data sharing for research, and the value of tailoring this to reflect current and local research where residents might feel more invested in the focus of research and the use of local records. Thus, the provision for targeted information within affected communities with accessible messages and community-based dialogue could help to build and sustain public trust. These findings can also be extrapolated to other conditions beyond musculoskeletal conditions, making the findings relevant to a much wider community. [ABSTRACT FROM AUTHOR]